- Machine Learning for Money Laundering Detection
Solution
AUSTRAC oversees the compliance of more than 15,000 reporting entities with their AML/CTF obligations, including reporting financial transactions and suspicious activity to AUSTRAC. AUSTRAC analyses…
- ML for Fraud Likelihood
Solution
Through a series of steps, the SEC is able to draw on machine learning applications to identify market misconduct and predict the likelihood of fraud. DERA – the Division of Economic and Risk…
- MuleHunter.ai
Solution · 10 December 2024
MuleHunter.AI, is an AI-powered tool to detect and flag mule accounts, helping reduce financial fraud and money laundering. Unlike traditional rule-based systems, MuleHunter.AI uses machine learning…
- Privacy-Preserving Data Collaboration
Solution
AUSTRAC is developing a proof of concept for a RegTech application that facilitates data collaboration without compromising data privacy to enhance its AML/CFT detection capabilities. The privacy…
- R²A AML Supervision
Open Code
An API program that provides data infrastructure for AML compliance. For this project, the Mexican National Banking and Securities Commission (CNBV) collaborated with R2A and Gestell to redesign its…
- RegTech & SupTech Innovation - IFWG Innovation Hub
Presentation
- SupTech: Cutting-Edge Innovation That’s Driving the Supervision of the Financial Sector
Blog · 15 May 2025
Regulatory bodies are deploying AI, ML, and blockchain to enhance oversight efficiency and detect risky banking behaviour in real-time. A study using data from the Central Bank of Brazil showed that…
- UK’s HMRC engages San Francisco-based ‘blockchain intelligence’ firm TRM Labs
News · 23 August 2024
HMRC is working with TRM Labs to help fight crypto-enabled money laundering. TRM Labs’ contract includes the provision of ‘analytical or scientific software’ and ‘investigation and security…
- United Kingdom’s HM Revenue & Customs (HMRC) engages San Fransisco-based ‘blockchain intelligence’ firm TRM Labs.
23 August 2024
HMRC is working with TRM Labs to help fight crypto-enabled money laundering. TRM Labs’ contract includes the provision of ‘analytical or scientific software’ and ‘investigation and security…
- Singapore plans ‘whole-of-government data-sharing interface’ to tackle money laundering.
4 November 2024
The plan is among the commitments in a ‘National Anti-Money Laundering (AML) Strategy’, jointly published by the Ministry of Finance, Ministry of Home Affairs and MAS on 30 October as part of…
- ML to Optimize Suspicious Transaction Detection
Blog
MAS is exploring how machine learning and aritificial intelligence can be applied to the investigation of suspicious transactions, a process that currently generates a high rate of false positives
- ML for Fraud Likelihood
Speech
Through a series of steps, the SEC is able to draw on machine learning applications to identify market misconduct and predict the likelihood of fraud. DERA – the Division of Economic and Risk…
- Machine Learning for Money Laundering Detection
News
AUSTRAC oversees the compliance of more than 15,000 reporting entities with their AML/CTF obligations, including reporting financial transactions and suspicious activity to AUSTRAC. AUSTRAC analyses…
- Hong Kong Customs partners with University of Hong Kong to develop cryptocurrency tracing tool
16 June 2025
The initiative responds to rising virtual asset-related money laundering, with seven suspected cases totalling over HKD 9 billion detected since 2021 out of 39 reported money laundering incidents.…
- Heavy Nodes in a Small Neighborhood: Algorithms and Applications
Open code repo by Kings College researchers looking at isolating suspicious AML activity by analysing a series of interrelated transactions for 'smurfing' activities
- Flowscope
Open Code
FlowScope is developed for ML detection based on multipartite graph, which models the high-volume flows of funds through chains of bank accounts, and detects the complete flow of money from source to…
- ER-20 Log Dataset
Open Data
This dataset contains transactions data from normal and phishing accounts, de-anonymized for analytics in Ethereum fraud detection
- Elliptic++
Open Data
The Elliptic++ dataset consists of 203k Bitcoin transactions and 822k wallet addresses to enable both the detection of fraudulent transactions and the detection of illicit addresses (actors) in the…
- Elliptic Plusplus
Open Data
This repository introduces a comprehensive applied data science approach to Bitcoin network fraud detection, leveraging the Elliptic++ dataset. Utilizing graph data, the repository employs four graph…
- Data analytics tools for supervising money services businesses
Video
Bank Negara Malaysia has developed advanced tools leveraging natural language processing and machine learning to enhance supervision of the money services business (MSB) sector, which is particularly…
- BERTH4ETH
Open Code
This GitHub repository houses code (TensorFlow version) and datasets for the paper "BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection," accepted at ACM Web conference (WWW) 2023…
- AUSTRAC unveils artificial intelligence (AI) transparency statement to combat financial crime
News · 28 March 2025
Australia's financial intelligence agency, AUSTRAC, has published its AI Transparency Statement, detailing how it employs AI to enhance detection of money laundering, terrorism financing and…
- Machine learning for anomaly detection in money services business outlets using data by geolocation
Report · 29 November 2024
Since 2017, licensed money services business (MSB) operators in Malaysia report transactional data to the Central Bank of Malaysia on a monthly basis. The data allow supervisors to conduct off-site…
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